π§ Coven
Collection
2 items
β’
Updated
Coven 7B 128K is an improved iteration of Mistral-7B-Instruct-v0.2, refined to expand processing capabilities and refine language model preferences. This model includes a significantly increased context constraint of 128K tokens using the Yarn technique, which allows for more extensive data processing and understanding of complex language scenarios. In addition, the Coven 7B ORPO 128K tokenization uses the innovative ORPO (Monolithic Preference Optimization without Reference Model) technology. ORPO simplifies the fine-tuning process by directly optimizing the odds ratio to distinguish between favorable and unfavorable generation styles, effectively improving model performance without the need for an additional preference alignment step.
Task | Model | Metric | Value | Change (%) |
---|---|---|---|---|
Winogrande | Mistral-7B-Instruct-v0.2 | Accuracy | 73.64% | - |
Coven 7B 128K ORPO | Accuracy | 77.82% | +5.67% | |
TruthfulQA | Mistral-7B-Instruct-v0.2 | Accuracy | 59.54% | - |
Coven 7B 128K ORPO | Accuracy | 49.55% | -16.78% | |
PIQA | Mistral-7B-Instruct-v0.2 | Accuracy | 80.03% | - |
Coven 7B 128K ORPO | Accuracy | 82.05% | +2.52% | |
OpenBookQA | Mistral-7B-Instruct-v0.2 | Accuracy | 36.00% | - |
Coven 7B 128K ORPO | Accuracy | 34.60% | -3.89% | |
Mistral-7B-Instruct-v0.2 | Accuracy Normalized | 45.20% | - | |
Coven 7B 128K ORPO | Accuracy Normalized | 48.00% | +6.19% | |
MMLU | Mistral-7B-Instruct-v0.2 | Accuracy | 58.79% | - |
Coven 7B 128K ORPO | Accuracy | 63.00% | +7.16% | |
Hellaswag | Mistral-7B-Instruct-v0.2 | Accuracy | 66.08% | - |
Coven 7B 128K ORPO | Accuracy | 65.37% | -1.08% | |
Mistral-7B-Instruct-v0.2 | Accuracy Normalized | 83.68% | - | |
Coven 7B 128K ORPO | Accuracy Normalized | 84.29% | +0.73% | |
GSM8K (Strict) | Mistral-7B-Instruct-v0.2 | Exact Match | 41.55% | - |
Coven 7B 128K ORPO | Exact Match | 72.18% | +73.65% | |
GSM8K (Flexible) | Mistral-7B-Instruct-v0.2 | Exact Match | 41.93% | - |
Coven 7B 128K ORPO | Exact Match | 72.63% | +73.29% | |
BoolQ | Mistral-7B-Instruct-v0.2 | Accuracy | 85.29% | - |
Coven 7B 128K ORPO | Accuracy | 87.43% | +2.51% | |
ARC Easy | Mistral-7B-Instruct-v0.2 | Accuracy | 81.36% | - |
Coven 7B 128K ORPO | Accuracy | 85.02% | +4.50% | |
Mistral-7B-Instruct-v0.2 | Accuracy Normalized | 76.60% | - | |
Coven 7B 128K ORPO | Accuracy Normalized | 82.95% | +8.29% | |
ARC Challenge | Mistral-7B-Instruct-v0.2 | Accuracy | 54.35% | - |
Coven 7B 128K ORPO | Accuracy | 59.64% | +9.74% | |
Mistral-7B-Instruct-v0.2 | Accuracy Normalized | 55.80% | - | |
Coven 7B 128K ORPO | Accuracy Normalized | 61.69% | +10.52% |
# Install transformers from source - only needed for versions <= v4.34
# pip install git+https://github.com/huggingface/transformers.git
# pip install accelerate
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="raidhon/coven_7b_128k_orpo_alpha", torch_dtype=torch.float16, device_map="auto")
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate",
},
{"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=4096, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])